Iterative Solution Methods

Martin Burger, Barbara Kaltenbacher and Andreas Neubauer
Additional contact information
Martin Burger: University of Mainz
Barbara Kaltenbacher: University of Graz
Andreas Neubauer: Karlsruhe Institute of Technology (KIT)

Chapter 9 in Handbook of Mathematical Methods in Imaging, 2011, pp 345-384 from Springer

Abstract: Abstract This chapter deals with iterative methods for nonlinear ill-posed problems. We present gradient and Newton type methods as well as nonstandard iterative algorithms such as Kaczmarz, expectation maximization, and Bregman iterations.Our intention here is to cite convergence results in the sense of regularization and to provide further references to the literature.

Keywords: Discrepancy Principle; Newton Method; Source Condition; Leibler Divergence; Newton Type Method (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-92920-0_9

Ordering information: This item can be ordered from
http://www.springer.com/9780387929200

DOI: 10.1007/978-0-387-92920-0_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().